By Topic

Chaos updating rotated gates quantum-inspired genetic algorithm

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Chen Hui ; Signal & Inf. Process. Key Lab. of Sichuan Province, Southwest Jiaotong Univ., Chengdu, China ; Zhang Jiashu ; Zhang Chao

From the recent research on combinational optimization of the knapsack problem, the quantum-inspired genetic algorithm (QGA) was proved to be better than conventional genetic algorithms. To accelerate the convergence speed of the QGA, the paper proposes research issues on QGA such as Q-gate. A novel Q-gate updating algorithm called chaos updating rotated gates quantum-inspired genetic algorithm (CQGA) is proposed. An analysis of the two main characters of quantum computing and chaos is also presented. This algorithm demonstrates the convergence of the quantum genetic algorithm (QGA). Several experiments are carried out on a class of numerical and combinatorial optimization problems. The results show the updated QGA makes QGA more powerful than the previous QGA in convergence speed.

Published in:

Communications, Circuits and Systems, 2004. ICCCAS 2004. 2004 International Conference on  (Volume:2 )

Date of Conference:

27-29 June 2004